In silico evaluation and exploration of antibiotic tuberculosis treatment regimens

BMC Systems Biology

Volumn 9, Issue 1, 2015, Pages

  Pienaar, Elsje ^a,b   Dartois, Véronique ^c   Linderman, Jennifer J ^a   Kirschner, Denise E ^b  

^a UNIVERSITY OF MICHIGAN   (United States)

^b UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

^c RUTGERS UNIVERSITY   (United States)

Author keywords

Computational model; Isoniazid; Pharmacokinetic Pharmacodynamic; Rifampin; Tissue distribution

Indexed keywords

ISONIAZID; RIFAMPICIN; TUBERCULOSTATIC AGENT;

ANIMAL; ANTIBIOTIC RESISTANCE; COMPUTER SIMULATION; GRANULOMA; GROWTH, DEVELOPMENT AND AGING; MICROBIOLOGY; MYCOBACTERIUM TUBERCULOSIS; TREATMENT OUTCOME; TUBERCULOSIS;

ANIMALS; ANTITUBERCULAR AGENTS; COMPUTER SIMULATION; DRUG RESISTANCE, BACTERIAL; GRANULOMA; ISONIAZID; MYCOBACTERIUM TUBERCULOSIS; RIFAMPIN; TREATMENT OUTCOME; TUBERCULOSIS;

EID: 84946963024     PISSN: None     EISSN: 17520509     Source Type: Journal    
DOI: 10.1186/s12918-015-0221-8     Document Type: Article

References (58)

1. WHO. Global tuberculosis report 2014.
2. Dartois V. The path of anti-tuberculosis drugs: from blood to lesions to mycobacterial cells. Nat Rev Microbiol. 2014;12(3):159-67. doi:10.1038/nrmicro3200.
3. Chang KC, Leung CC, Grosset J, Yew WW. Treatment of tuberculosis and optimal dosing schedules. Thorax. 2011;66(11):997-1007. doi:10.1136/thx.2010.148585.
4. Zumla A, Nahid P, Cole ST. Advances in the development of new tuberculosis drugs and treatment regimens. Nat Rev Drug Discov. 2013;12(5):388-404. doi:10.1038/nrd4001.
5. Saltini C. Schedule or dosage? The need to perfect intermittent regimens for tuberculosis. Am J Respir Crit Care Med. 2006;174(10):1067-8. doi:10.1164/rccm.200608-1194ED.
6. Nimmo C, Lipman M, Phillips PP, McHugh T, Nunn A, Abubakar I. Shortening treatment of tuberculosis: lessons from fluoroquinolone trials. Lancet Infect Dis. 2015;15(2):141-3. doi:10.1016/S1473-3099(14)70885-0.
7. Warner DF, Mizrahi V. Shortening treatment for tuberculosis-to basics. N Engl J Med. 2014;371(17):1642-3. doi:10.1056/NEJMe1410977.
8. Menzies D, Benedetti A, Paydar A, Royce S, Madhukar P, Burman W, et al. Standardized treatment of active tuberculosis in patients with previous treatment and/or with mono-resistance to isoniazid: a systematic review and meta-analysis. PLoS Med. 2009;6(9), e1000150.
9. Bose A, Kalita S, Rose W, Tharyan P. Intermittent versus daily therapy for treating tuberculosis in children. Cochrane Database Syst Rev. 2014;1:CD007953. doi:10.1002/14651858.CD007953.pub2.
10. Zumla AI, Gillespie SH, Hoelscher M, Philips PP, Cole ST, Abubakar I, et al. New antituberculosis drugs, regimens, and adjunct therapies: needs, advances, and future prospects. Lancet Infect Dis. 2014;14(4):327-40. doi:10.1016/S1473-3099(13)70328-1.
11. Merle CS, Fielding K, Sow OB, Gninafon M, Lo MB, Mthiyane T, et al. A four-month gatifloxacin-containing regimen for treating tuberculosis. N Engl J Med. 2014;371(17):1588-98. doi:10.1056/NEJMoa1315817.
12. Jindani A, Harrison TS, Nunn AJ, Phillips PP, Churchyard GJ, Charalambous S, et al. High-dose rifapentine with moxifloxacin for pulmonary tuberculosis. N Engl J Med. 2014;371(17):1599-608. doi:10.1056/NEJMoa1314210.
13. Gillespie SH, Crook AM, McHugh TD, Mendel CM, Meredith SK, Murray SR, et al. Four-month moxifloxacin-based regimens for drug-sensitive tuberculosis. N Engl J Med. 2014;371(17):1577-87. doi:10.1056/NEJMoa1407426.
14. Kjellsson MC, Via LE, Goh A, Weiner D, Low KM, Kern S, et al. Pharmacokinetic evaluation of the penetration of antituberculosis agents in rabbit pulmonary lesions. Antimicrob Agents Chemother. 2012;56(1):446-57. doi:10.1128/AAC.05208-11.
15. Cilfone NA, Ford CB, Marino S, Mattila JT, Gideon HP, Flynn J, et al. Computational modeling predicts interleukin-10 control of lesion sterilization by balancing early host-immunity-mediated antimicrobial responses with caseation during mycobacterium tuberculosis infection. J Immunol. 2015;194(2):664-77. doi:10.4049/jimmunol.1400734.
16. Cilfone NA, Perry CR, Kirschner DE, Linderman JJ. Multi-scale modeling predicts a balance of tumor necrosis factor-alpha and interleukin-10 controls the granuloma environment during Mycobacterium tuberculosis infection. PLoS One. 2013;8(7):e68680. doi:10.1371/journal.pone.0068680.
17. Fallahi-Sichani M, El-Kebir M, Marino S, Kirschner DE, Linderman JJ. Multiscale computational modeling reveals a critical role for TNF-alpha receptor 1 dynamics in tuberculosis granuloma formation. J Immunol. 2011;186(6):3472-83. doi:10.4049/jimmunol.1003299.
18. Fallahi-Sichani M, Flynn JL, Linderman JJ, Kirschner DE. Differential risk of tuberculosis reactivation among anti-TNF therapies is due to drug binding kinetics and permeability. J Immunol. 2012;188(7):3169-78. doi:10.4049/jimmunol.1103298.
19. Ray JC, Flynn JL, Kirschner DE. Synergy between individual TNF-dependent functions determines granuloma performance for controlling Mycobacterium tuberculosis infection. J Immunol. 2009;182(6):3706-17. doi:10.4049/jimmunol.0802297.
20. Pienaar E, Cilfone NA, Lin PL, Dartois V, Mattila JT, Butler JR, et al. A computational tool integrating host immunity with antibiotic dynamics to study tuberculosis treatment. J Theor Biol. 2015;367:166-79. doi:10.1016/j.jtbi.2014.11.021.
21. Lin PL, Rodgers M, Smith L, Bigbee M, Myers A, Bigbee C, et al. Quantitative comparison of active and latent tuberculosis in the cynomolgus macaque model. Infect Immun. 2009;77(10):4631-42. doi:10.1128/IAI.00592-09.
22. Blumberg HM, Burman WJ, Chaisson RE, Daley CL, Etkind SC, Friedman LN, et al. American Thoracic Society/Centers for Disease Control and Prevention/Infectious Diseases Society of America: treatment of tuberculosis. Am J Respir Crit Care Med. 2003;167(4):603-62. doi:10.1164/rccm.167.4.603.
23. Lin PL, Dartois V, Johnston PJ, Janssen C, Via L, Goodwin MB, et al. Metronidazole prevents reactivation of latent Mycobacterium tuberculosis infection in macaques. Proc Natl Acad Sci U S A. 2012;109(35):14188-93. doi:10.1073/pnas.1121497109.
24. Flynn JL, Gideon HP, Mattila JT, Lin PL. Immunology studies in non-human primate models of tuberculosis. Immunol Rev. 2015;264(1):60-73. doi:10.1111/imr.12258.
25. Jayaram R, Gaonkar S, Kaur P, Suresh BL, Mahesh BN, Jayashree R, et al. Pharmacokinetics-pharmacodynamics of rifampin in an aerosol infection model of tuberculosis. Antimicrob Agents Chemother. 2003;47(7):2118-24.
26. Jayaram R, Shandil RK, Gaonkar S, Kaur P, Suresh BL, Mahesh BN, et al. Isoniazid pharmacokinetics-pharmacodynamics in an aerosol infection model of tuberculosis. Antimicrob Agents Chemother. 2004;48(8):2951-7. doi:10.1128/AAC.48.8.2951-2957.2004.
27. de Steenwinkel JE, de Knegt GJ, ten Kate MT, van Belkum A, Verbrugh HA, Kremer K, et al. Time-kill kinetics of anti-tuberculosis drugs, and emergence of resistance, in relation to metabolic activity of Mycobacterium tuberculosis. J Antimicrob Chemother. 2010;65(12):2582-9. doi:10.1093/jac/dkq374.
28. Gumbo T, Louie A, Deziel MR, Liu W, Parsons LM, Salfinger M, et al. Concentration-dependent Mycobacterium tuberculosis killing and prevention of resistance by rifampin. Antimicrob Agents Chemother. 2007;51(11):3781-8. doi:10.1128/AAC.01533-06.
29. Gumbo T, Louie A, Liu W, Brown D, Ambrose PG, Bhavnani SM, et al. Isoniazid bactericidal activity and resistance emergence: integrating pharmacodynamics and pharmacogenomics to predict efficacy in different ethnic populations. Antimicrob Agents Chemother. 2007;51(7):2329-36. doi:10.1128/AAC.00185-07.
30. Lin PL, Coleman T, Carney JP, Lopresti BJ, Tomko J, Fillmore D et al. Radiologic responses in cynomolgous macaques for assessing tuberculosis chemotherapy regimens. Antimicrob Agents Chemother. 2013. doi:10.1128/AAC.00277-13.
31. Devarbhavi H. Antituberculous drug-induced liver injury: current perspective. Trop Gastroenterol. 2011;32(3):167-74.
32. Ruslami R, Ganiem AR, Dian S, Apriani L, Achmad TH, van der Ven AJ, et al. Intensified regimen containing rifampicin and moxifloxacin for tuberculous meningitis: an open-label, randomised controlled phase 2 trial. Lancet Infect Dis. 2013;13(1):27-35. doi:10.1016/S1473-3099(12)70264-5.
33. Possuelo LG, Castelan JA, de Brito TC, Ribeiro AW, Cafrune PI, Picon PD, et al. Association of slow N-acetyltransferase 2 profile and anti-TB drug-induced hepatotoxicity in patients from Southern Brazil. Eur J Clin Pharmacol. 2008;64(7):673-81. doi:10.1007/s00228-008-0484-8.
34. Menzies D, Benedetti A, Paydar A, Martin I, Royce S, Pai M, et al. Effect of duration and intermittency of rifampin on tuberculosis treatment outcomes: a systematic review and meta-analysis. PLoS Med. 2009;6(9):e1000146. doi:10.1371/journal.pmed.1000146.
35. McFee RB. Update-pathogens of concern. Dis Mon. 2013;59(12):437-8. doi:10.1016/j.disamonth.2013.10.006.
36. Frieden T. Toman's tuberculosis: case detection, treatment and monitoring: questions and answers. 2nd ed. Geneva, Switzerland: WHO; 2004.
37. Chang KC, Leung CC, Yew WW, Chan SL, Tam CM. Dosing schedules of 6-month regimens and relapse for pulmonary tuberculosis. Am J Respir Crit Care Med. 2006;174(10):1153-8. doi:10.1164/rccm.200605-637OC.
38. Chang KC, Leung CC, Yew WW, Ho SC, Tam CM. A nested case-control study on treatment-related risk factors for early relapse of tuberculosis. Am J Respir Crit Care Med. 2004;170(10):1124-30. doi:10.1164/rccm.200407-905OC.
39. Boeree MJ, Diacon AH, Dawson R, Narunsky K, du Bois J, Venter A et al. A Dose Ranging Trial to Optimize the Dose of Rifampin in the Treatment of Tuberculosis. Am J Respir Crit Care Med. 2015. doi:10.1164/rccm.201407-1264OC.
40. Srivastava S, Pasipanodya JG, Meek C, LeffR, Gumbo T. Multidrug-resistant tuberculosis not due to noncompliance but to between-patient pharmacokinetic variability. J Infect Dis. 2011;204(12):1951-9. doi:10.1093/infdis/jir658.
41. Dartois V. Drug forgiveness and interpatient pharmacokinetic variability in tuberculosis. J Infect Dis. 2011;204(12):1827-9. doi:10.1093/infdis/jir662.
42. Boeree MJ, Plemper Van Balen G, Aarnoutse RA. High-dose rifampicin: how do we proceed? Int J Tuberc Lung Dis. 2011;15(8):1133. doi:10.5588/ijtld.11.0198.
43. Wright J, Walley J, Philip A, Pushpananthan S, Dlamini E, Newell J, et al. Direct observation of treatment for tuberculosis: a randomized controlled trial of community health workers versus family members. Trop Med Int Health. 2004;9(5):559-65. doi:10.1111/j.1365-3156.2004.01230.x.
44. Wandwalo E, Makundi E, Hasler T, Morkve O. Acceptability of community and health facility-based directly observed treatment of tuberculosis in Tanzanian urban setting. Health Policy. 2006;78(2-3):284-94. doi:10.1016/j.healthpol.2005.11.010.
45. Dartois V, Barry 3rd CE. A medicinal chemists' guide to the unique difficulties of lead optimization for tuberculosis. Bioorg Med Chem Lett. 2013;23(17):4741-50. doi:10.1016/j.bmcl.2013.07.006.
46. Martins F, Ventura C, Santos S, Viveiros M. QSAR based design of new antitubercular compounds: improved isoniazid derivatives against multidrug-resistant TB. Curr Pharm Des. 2014;20(27):4427-54.
47. Rajkhowa S, Deka RC. DFT based QSAR/QSPR models in the development of novel anti-tuberculosis drugs targeting Mycobacterium tuberculosis. Curr Pharm Des. 2014;20(27):4455-73.
48. Hearn MJ, Cynamon MH. Design and synthesis of antituberculars: preparation and evaluation against Mycobacterium tuberculosis of an isoniazid Schiffbase. J Antimicrob Chemother. 2004;53(2):185-91. doi:10.1093/jac/dkh041.
49. Churchyard GJ, Kaplan G, Fallows D, Wallis RS, Onyebujoh P, Rook GA. Advances in immunotherapy for tuberculosis treatment. Clin Chest Med. 2009;30(4):769-82. ix. doi:10.1016/j.ccm.2009.08.009.
50. Saifullah B, Hussein MZ. Hussein Al Ali SH. Controlled-release approaches towards the chemotherapy of tuberculosis. Int J Nanomedicine. 2012;7:5451-63. doi:10.2147/IJN.S34996.
51. Cilfone NA, Pienaar E, Thurber GM, Kirschner DE, Linderman JJ. A systems pharmacology approach towards the design of inhaled formulations of rifampicin and isoniazid for treatment of tuberculosis. CPT: Pharmacometrics and systems pharmacology. 2015;In Press.
52. Datta M, Via LE, Kamoun WS, Liu C, Chen W, Seano G et al. Anti-vascular endothelial growth factor treatment normalizes tuberculosis granuloma vasculature and improves small molecule delivery. Proc Natl Acad Sci U S A. 2015 doi:10.1073/pnas.1424563112.
53. Cilfone NA, Kirschner DE, Linderman JJ. Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems. Cellular Mol Bioeng. 2014;8(1):119-36.
54. Goutelle S, Bourguignon L, Maire PH, Van Guilder M, Conte Jr JE, Jelliffe RW. Population modeling and Monte Carlo simulation study of the pharmacokinetics and antituberculosis pharmacodynamics of rifampin in lungs. Antimicrob Agents Chemother. 2009;53(7):2974-81. doi:10.1128/AAC.01520-08.
55. Bouvier d'Yvoire MY, Maire P. Dosage Regimens of Antibacterials. Clin Drug Invest. 1996;11(4):229-39. doi:10.2165/00044011-199611040-00006.
56. Dickinson JM, Aber VR, Mitchison DA. Bactericidal activity of streptomycin, isoniazid, rifampin, ethambutol, and pyrazinamide alone and in combination against Mycobacterium Tuberculosis. Am Rev Respir Dis. 1977;116(4):627-35.
57. Bhusal Y, Shiohira CM, Yamane N. Determination of in vitro synergy when three antimicrobial agents are combined against Mycobacterium tuberculosis. Int J Antimicrob Agents. 2005;26(4):292-7. doi:10.1016/j.ijantimicag.2005.05.005.
58. Bergval IL, Schuitema AR, Klatser PR, Anthony RM. Resistant mutants of Mycobacterium tuberculosis selected in vitro do not reflect the in vivo mechanism of isoniazid resistance. J Antimicrob Chemother. 2009;64(3):515-23. doi:10.1093/jac/dkp237